Abstract
As fundamental resources of research activities, data is vitally important for scientific progress and general social society. Thus, open data practices are becoming more prevalent and the adoption of the FAIR (Findable, Accessible, Interoperable, and Reusable) principles is fostering open access data from four general perspectives. This paper firstly analyzes the general benefits and necessities of open data and the FAIR principles. Then, data policies in China are described from four views. Subsequently, challenges and opportunities for data usability across disciplinary boundaries and levels of expertise are described. Finally, categories are presented for how data policies in China enable FAIR data in terms of the four views of Chinese data policies. Above all, FAIR data is a good beginning, and for FAIR open data, we still need more efforts on intrinsic data culture, trustworthiness, sustainability, and multilateral cooperation among various stakeholders, as well as consistent and effective approaches for adopting data policies.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Borgman, C.L.: The conundrum of sharing research data. J. Am. Soc. Inf. Sci. Technol. 63(6), 1059–1078 (2012). https://doi.org/10.1002/asi.22634
Barbui, C., Gureje, O., Puschner, B., et al.: Implementing a data sharing culture. Epidemiol. Psychiatr. Sci. 25, 289–290 (2016). https://doi.org/10.1017/S2045796016000330
CoreTrustSeal: Data Repositories Requirements (n.d.). https://www.coretrustseal.org/why-certification/requirements/. Accessed 8 Jan 2019
Doshi, J.A., Hendrick, F.B., Graff, J.S., et al.: Data, data everywhere, but access remains a big issue for researchers: a review of access policies for publicly funded patient-level health care data in the United States. EDM Forum Community 4(2), 1–20 (2016). https://doi.org/10.13063/2327-9214.1204
Edmunds, S.C., Li, P., Hunter, C.I., et al.: Experiences in integrated data and research object publishing using GigaDB. Int. J. Digit. Libr. (2016). https://doi.org/10.1007/s00799-016-0174-6
Faniel, I.M., Zimmerman, A.: Beyond the data deluge: a research agenda. Int. J. Digit. Curation 6(1), 58–69 (2011)
HXMT: Data policy of HXMT (2018). http://www.hxmt.org/index.php/2013-03-22-08-08-48/docs/319-hxmt-data-polocy-of-hxmt. Accessed 29 Dec 2018. (in Chinese)
Kaye, J., Heeney, C., Hawkins, N., et al.: Data sharing in genomics-re-shaping scientific practice. Nat. Rev. Genet. 10, 331–335 (2009)
Lamost: Lamost DR 6 V1 (2018). http://dr6.lamost.org/. Accessed 29 Dec 2018
Longo, D.L., Drazen, J.M.: Data sharing. New Engl. J. Med. 374(3), 276–277 (2016)
General Office of the State Council, China: Measures for Managing Scientific Data (2018). http://www.gov.cn/zhengce/content/2018-04/02/content_5279272.htm. Accessed 9 Jan 2019
OECD: Business models for sustainable research data repositories. OECD Science, Technology and Industry Policy Papers, No. 47. OECD Publishing, Paris (2017). https://doi.org/10.1787/302b12bb-en
Peng, G.: The state of assessing data stewardship maturity – an overview. Data Sci. J. 17, 7 (2018). https://doi.org/10.5334/dsj-2018-00
Feng, H.: Interpretation of the first national level Measures for managing scientific data. People’s Daily, 8 April 2018. http://www.xinhuanet.com/politics/2018-04/08/c_1122647406.htm. Accessed 9 Jan 2019. (in Chinese)
Wilkinson, M., Dumontier, M., Aalbersberg, I., et al.: The FAIR guiding principles for scientific data management and stewardship. Nat. Sci. Data 3(2016). https://doi.org/10.1038/sdata.2016.18
Acknowledgements
This work is an outcome of the project of “International and National Scientific Data Resources Development Report in China 2018” (No. 2018DDJ1ZZ14) supported by the National Science and Technology Infrastructure Center, and the project “Decision Making Oriented Massive Data Resources Sharing and Governance” (No. 91546125) supported by National Natural Science Foundation of China, and “Big data resources pool and system portal” (No. XDA19020104) funded by the Chinese Academy of Sciences.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Zhang, L., Downs, R.R., Li, J. (2019). Changing Data Policies in China: Implications for Enabling FAIR Data. In: Li, J., Meng, X., Zhang, Y., Cui, W., Du, Z. (eds) Big Scientific Data Management. BigSDM 2018. Lecture Notes in Computer Science(), vol 11473. Springer, Cham. https://doi.org/10.1007/978-3-030-28061-1_28
Download citation
DOI: https://doi.org/10.1007/978-3-030-28061-1_28
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-28060-4
Online ISBN: 978-3-030-28061-1
eBook Packages: Computer ScienceComputer Science (R0)